Animals and artificial systems alike are faced with the problem of making inferences about their environments and choosing appropriate responses based on incomplete, uncertain and noisy data.

Probabilistic models and algorithms are flourishing in both life sciences an information sciences as ways of understanding the behavior of subjects and the neural processing underlying this behavior, and building robots and artificial agents that can function effectively in such circumstances.

The Bayesian Cognition community organizes events to prospect, discuss and study these topics